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Updated: May 20, 2025

Retroductal Submandibular Gland Instillation and Localized Fractionated Irradiation in a Rat Model of Salivary Hypofunction
Published on: April 24, 2016
Mechanisms Tackling Salivary Gland Diseases with Extracellular Vesicle Therapies
P Sawutdeechaikul1, S Hwang2, J Klangprapan1
1Center of Excellence and Innovation for Oral Health and Health Longevity, Faculty of Dentistry, Chulalongkorn University, Bangkok, Thailand.
Abstract:
Extracellular vesicles (EVs) are lipid-enclosed particles released from cells, containing lipids, DNA, RNA, metabolites, and cytosolic and cell surface proteins. EVs support intercellular communication and orchestrate organogenesis by transferring bioactive molecules in between cells. Mesenchymal stem cells are known to produce EVs, which exhibit immunomodulatory and regenerative capabilities in many target organs, including the salivary glands (SGs). Since cell-based therapies still pose challenges (e.g., donor variability, limited hemocompatibility, and safety), specific EVs may constitute a therapeutic alternative for SG diseases. New EV guidelines (MISEV2023) have recently been updated and reported by our consortium to consolidate the principles of EV biology and expand the boundaries toward innovative therapies. These guidelines provide valuable guidance for researchers to consistently assess the effectiveness of mesenchymal stem cell-derived EV cargo cues, such as microRNA, proteins, and other molecules, to target SG diseases. This review provides a narrative synthesis of preclinical studies on EVs by highlighting EV mechanisms and their potential therapeutic applications for SG diseases, such as radiotherapy-induced SG hypofunction and Sjögren's syndrome, as well as inflammatory and aging-related SG conditions. Additionally, we highlight key areas of the MISEV2023 guidelines that will support future EV-based therapies in SG research. This review adhered to PRESS guidelines (Peer Review of Electronic Search Strategies) and utilized established databases, including Medline/PubMed, Embase, Web of Science, and Scopus, alongside machine learning tools for sorting the most impactful EV studies for SG diseases.
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